JAGS中的贝叶斯IRT:教程

Kenneth McClure
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引用次数: 0

摘要

项目反应模型在智力、精神病理和能力评估的心理学和教育中是常见的。本文提供了在贝叶斯框架下估计双参数logistic和梯度响应模型的教程,并介绍了在该框架下评估收敛性和模型拟合。示例数据来自2017年全国青年纵向调查浪潮中的抑郁项目,并为JAGS提供了示例代码,并使用runjags包通过R实现。本文的目的是为读者提供在JAGS中进行贝叶斯IRT的必要信息。
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Bayesian IRT in JAGS: A Tutorial
Item response modeling is common throughout psychology and education in assessments of intelligence, psychopathology, and ability. The current paper provides a tutorial on estimating the two-parameter logistic and graded response models in a Bayesian framework as well as provide an introduction on evaluating convergence and model fit in this framework. Example data are drawn from depression items in the 2017 Wave of the National Longitudinal Survey of Youth and example code is provided for JAGS and implemented through R using the runjags package. The aim of this paper is to provide readers with the necessary information to conduct Bayesian IRT in JAGS.
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